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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- minds14 |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-finetuned-minds-1 |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: minds14 |
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type: minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7610619469026548 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-base-finetuned-minds-1 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4208 |
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- Accuracy: 0.7611 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.6059 | 1.0 | 57 | 2.5954 | 0.0973 | |
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| 2.5183 | 2.0 | 114 | 2.5787 | 0.0973 | |
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| 2.5497 | 3.0 | 171 | 2.5629 | 0.1416 | |
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| 2.3827 | 4.0 | 228 | 2.5407 | 0.1858 | |
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| 2.309 | 5.0 | 285 | 2.3023 | 0.2301 | |
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| 2.0098 | 6.0 | 342 | 2.0528 | 0.3540 | |
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| 1.797 | 7.0 | 399 | 1.8558 | 0.4602 | |
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| 1.4416 | 8.0 | 456 | 1.6847 | 0.5841 | |
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| 1.3491 | 9.0 | 513 | 1.4911 | 0.6991 | |
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| 1.3468 | 10.0 | 570 | 1.4208 | 0.7611 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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